Neurophysiological consequences of synapse loss in progressive supranuclear palsy.

Synaptic loss occurs early in many neurodegenerative diseases and contributes to cognitive impairment even in the absence of gross atrophy. Currently, for human disease there are few formal models to explain how cortical networks underlying cognition are affected by synaptic loss. We advocate that biophysical models of neurophysiology offer both a bridge from preclinical to clinical models of pathology and quantitative assays for experimental medicine. Such biophysical models can also disclose hidden neuronal dynamics generating neurophysiological observations such as EEG and magnetoencephalography. Here, we augment a biophysically informed mesoscale model of human cortical function by inclusion of synaptic density estimates as captured by 11C-UCB-J PET, and provide insights into how regional synapse loss affects neurophysiology. We use the primary tauopathy of progressive supranuclear palsy (Richardson's syndrome) as an exemplar condition, with high clinicopathological correlations. Progressive supranuclear palsy causes a marked change in cortical neurophysiology in the presence of mild cortical atrophy and is associated with a decline in cognitive functions associated with the frontal lobe. Using parametric empirical Bayesian inversion of a conductance-based canonical microcircuit model of magnetoencephalography data, we show that the inclusion of regional synaptic density-as a subject-specific prior on laminar-specific neuronal populations-markedly increases model evidence. Specifically, model comparison suggests that a reduction in synaptic density in inferior frontal cortex affects superficial and granular layer glutamatergic excitation. This predicted individual differences in behaviour, demonstrating the link between synaptic loss, neurophysiology and cognitive deficits. The method we demonstrate is not restricted to progressive supranuclear palsy or the effects of synaptic loss: such pathology-enriched dynamic causal models can be used to assess the mechanisms of other neurological disorders, with diverse non-invasive measures of pathology, and is suitable to test the effects of experimental pharmacology.

Left Prefrontal Connectivity Links Subthalamic Stimulation with Depressive Symptoms.

OBJECTIVE: Subthalamic nucleus deep brain stimulation (STN-DBS) in Parkinson's disease (PD) not only stimulates focal target structures but also affects distributed brain networks. The impact this network modulation has on non-motor DBS effects is not well-characterized. By focusing on the affective domain, we systematically investigate the impact of electrode placement and associated structural connectivity on changes in depressive symptoms following STN-DBS, which have been reported to improve, worsen, or remain unchanged. METHODS: Depressive symptoms before and after STN-DBS surgery were documented in 116 patients with PD from 3 DBS centers (Berlin, Queensland, and Cologne). Based on individual electrode reconstructions, the volumes of tissue activated (VTAs) were estimated and combined with normative connectome data to identify structural connections passing through VTAs. Berlin and Queensland cohorts formed a training and cross-validation dataset used to identify structural connectivity explaining change in depressive symptoms. The Cologne data served as the test-set for which depressive symptom change was predicted. RESULTS: Structural connectivity was linked to depressive symptom change under STN-DBS. An optimal connectivity map trained on the Berlin cohort could predict changes in depressive symptoms in Queensland patients and vice versa. Furthermore, the joint training-set map predicted changes in depressive symptoms in the independent test-set. Worsening of depressive symptoms was associated with left prefrontal connectivity. INTERPRETATION: Fibers connecting the electrode with left prefrontal areas were associated with worsening of depressive symptoms. Our results suggest that for the left STN-DBS lead, placement impacting fibers to left prefrontal areas should be avoided to maximize improvement of depressive symptoms. ANN NEUROL 2020;87:962-975.

The structural connectivity of subthalamic deep brain stimulation correlates with impulsivity in Parkinson's disease.

Subthalamic deep brain stimulation (STN-DBS) for Parkinson's disease treats motor symptoms and improves quality of life, but can be complicated by adverse neuropsychiatric side-effects, including impulsivity. Several clinically important questions remain unclear: can 'at-risk' patients be identified prior to DBS; do neuropsychiatric symptoms relate to the distribution of the stimulation field; and which brain networks are responsible for the evolution of these symptoms? Using a comprehensive neuropsychiatric battery and a virtual casino to assess impulsive behaviour in a naturalistic fashion, 55 patients with Parkinson's disease (19 females, mean age 62, mean Hoehn and Yahr stage 2.6) were assessed prior to STN-DBS and 3 months postoperatively. Reward evaluation and response inhibition networks were reconstructed with probabilistic tractography using the participant-specific subthalamic volume of activated tissue as a seed. We found that greater connectivity of the stimulation site with these frontostriatal networks was related to greater postoperative impulsiveness and disinhibition as assessed by the neuropsychiatric instruments. Larger bet sizes in the virtual casino postoperatively were associated with greater connectivity of the stimulation site with right and left orbitofrontal cortex, right ventromedial prefrontal cortex and left ventral striatum. For all assessments, the baseline connectivity of reward evaluation and response inhibition networks prior to STN-DBS was not associated with postoperative impulsivity; rather, these relationships were only observed when the stimulation field was incorporated. This suggests that the site and distribution of stimulation is a more important determinant of postoperative neuropsychiatric outcomes than preoperative brain structure and that stimulation acts to mediate impulsivity through differential recruitment of frontostriatal networks. Notably, a distinction could be made amongst participants with clinically-significant, harmful changes in mood and behaviour attributable to DBS, based upon an analysis of connectivity and its relationship with gambling behaviour. Additional analyses suggested that this distinction may be mediated by the differential involvement of fibres connecting ventromedial subthalamic nucleus and orbitofrontal cortex. These findings identify a mechanistic substrate of neuropsychiatric impairment after STN-DBS and suggest that tractography could be used to predict the incidence of adverse neuropsychiatric effects. Clinically, these results highlight the importance of accurate electrode placement and careful stimulation titration in the prevention of neuropsychiatric side-effects after STN-DBS.

Subthalamic deep brain stimulation identifies frontal networks supporting initiation, inhibition and strategy use in Parkinson's disease.

Initiation and inhibition are executive functions whose disruption in Parkinson's disease impacts substantially on everyday activities. Management of Parkinson's disease with subthalamic deep brain stimulation (DBS) modifies initiation and inhibition, with prior work suggesting that these effects may be mediated via the connectivity of the subthalamic nucleus (STN) with the frontal cortex. Here, we employed high-resolution structural neuroimaging to investigate the variability in initiation, inhibition and strategy use in a cohort of twenty-five (ten females, mean age 62.5, mean Hoehn and Yahr stage 2.5) participants undertaking subthalamic DBS for Parkinson's disease. Neuropsychological assessment of initiation and inhibition was performed preoperatively and at six months postoperatively. We first reconstructed the preoperative connectivity of the STN with a frontal network of anterior and superior medial cortical regions. We then modelled the postoperative site of subthalamic stimulation and reconstructed the connectivity of the stimulation field within this same network. We found that, at both pre- and postoperative intervals, inter-individual variability in inhibition and initiation were strongly associated with structural network connectivity. Measures of subcortical atrophy and local stimulation effects did not play a significant role. Preoperatively, we replicated prior work, including a role for the right inferior frontal gyrus in inhibition and strategy use, as well as the left inferior frontal gyrus in tasks requiring selection under conditions of maintained inhibition. Postoperatively, greater connectivity of the stimulation field with right anterior cortical regions was associated with greater rule violations and suppression errors, supporting prior work implicating right-hemispheric STN stimulation in disinhibition. Our findings suggest that, in Parkinson's disease, connectivity of the frontal cortex with the STN is an important mediator of individual variability in initiation and inhibition,. Personalised information on brain network architecture could guide individualised brain circuit manipulation to minimise neuropsychological disruption after STN-DBS.

Connectomics of bipolar disorder: a critical review, and evidence for dynamic instabilities within interoceptive networks.

The notion that specific cognitive and emotional processes arise from functionally distinct brain regions has lately shifted toward a connectivity-based approach that emphasizes the role of network-mediated integration across regions. The clinical neurosciences have likewise shifted from a predominantly lesion-based approach to a connectomic paradigm-framing disorders as diverse as stroke, schizophrenia (SCZ), and dementia as "dysconnection syndromes". Here we position bipolar disorder (BD) within this paradigm. We first summarise the disruptions in structural, functional and effective connectivity that have been documented in BD. Not surprisingly, these disturbances show a preferential impact on circuits that support emotional processes, cognitive control and executive functions. Those at high risk (HR) for BD also show patterns of connectivity that differ from both matched control populations and those with BD, and which may thus speak to neurobiological markers of both risk and resilience. We highlight research fields that aim to link brain network disturbances to the phenotype of BD, including the study of large-scale brain dynamics, the principles of network stability and control, and the study of interoception (the perception of physiological states). Together, these findings suggest that the affective dysregulation of BD arises from dynamic instabilities in interoceptive circuits which subsequently impact on fear circuitry and cognitive control systems. We describe the resulting disturbance as a "psychosis of interoception".

Correction: Connectomics of bipolar disorder: a critical review, and evidence for dynamic instabilities within interoceptive networks.

This Article was originally published under Nature Research's License to Publish, but has now been made available under a [CC BY 4.0] license. The PDF and HTML versions of the Article have been modified accordingly.

The structural connectivity of discrete networks underlies impulsivity and gambling in Parkinson's disease.

Impulsivity in Parkinson's disease may be mediated by faulty evaluation of rewards or the failure to inhibit inappropriate choices. Despite prior work suggesting that distinct neural networks underlie these cognitive operations, there has been little study of these networks in Parkinson's disease, and their relationship to inter-individual differences in impulsivity. High-resolution diffusion MRI data were acquired from 57 individuals with Parkinson's disease (19 females, mean age 62, mean Hoehn and Yahr stage 2.6) prior to surgery for deep brain stimulation. Reward evaluation and response inhibition networks were reconstructed with seed-based probabilistic tractography. Impulsivity was evaluated using two approaches: (i) neuropsychiatric instruments were used to assess latent constructs of impulsivity, including trait impulsiveness and compulsivity, disinhibition, and also impatience; and (ii) participants gambled in an ecologically-valid virtual casino to obtain a behavioural read-out of explorative, risk-taking, impulsive behaviour. Multivariate analyses revealed that different components of impulsivity were associated with distinct variations in structural connectivity, implicating both reward evaluation and response inhibition networks. Larger bet sizes in the virtual casino were associated with greater connectivity of the reward evaluation network, particularly bilateral fibre tracts between the ventral striatum and ventromedial prefrontal cortex. In contrast, weaker connectivity of the response inhibition network was associated with increased exploration of alternative slot machines in the virtual casino, with right-hemispheric tracts between the subthalamic nucleus and the pre-supplementary motor area contributing most strongly. Further, reduced connectivity of the reward evaluation network was associated with more 'double or nothing' gambles, weighted by connections between the subthalamic nucleus and ventromedial prefrontal cortex. Notably, the variance explained by structural connectivity was higher for behavioural indices of impulsivity, derived from clinician-administered tasks and the gambling paradigm, as compared to questionnaire data. Lastly, a clinically-meaningful distinction could be made amongst participants with a history of impulse control behaviours based on the interaction of their network connectivity with medication dosage and gambling behaviour. In summary, we report structural brain-behaviour covariation in Parkinson's disease with distinct reward evaluation and response inhibition networks that underlie dissociable aspects of impulsivity (cf. choosing and stopping). More broadly, our findings demonstrate the potential of using naturalistic paradigms and neuroimaging techniques in clinical settings to assist in the identification of those susceptible to harmful behaviours.

Local temporal variability reflects functional integration in the human brain.

Local moment-to-moment variability exists at every level of neural organization, but its driving forces remain opaque. Inspired by animal work demonstrating that local temporal variability may reflect synaptic input rather than locally-generated "noise," we used publicly-available high-temporal-resolution fMRI data (N = 100 adults; 33 males) to test in humans whether greater BOLD signal variability in local brain regions was associated with functional integration (estimated via spatiotemporal PCA dimensionality). Using a multivariate partial least squares analysis, we indeed found that individuals with higher local temporal variability had a more integrated (lower dimensional) network fingerprint. Notably, temporal variability in the thalamus showed the strongest negative association with PCA dimensionality. Previous animal work also shows that local variability may upregulate from thalamus to visual cortex; however, such principled upregulation from thalamus to cortex has not been demonstrated in humans. In the current study, we rather establish a more general putative dynamic role of the thalamus by demonstrating that greater within-person thalamo-cortical upregulation in variability is itself a unique hallmark of greater functional integration that cannot be accounted for by local fluctuations in several other well-known integrative-hub regions. Our findings indicate that local variability primarily reflects functional integration, and establish a fundamental role for the thalamus in how the brain fluctuates and communicates across moments.

Brain-behavior patterns define a dimensional biotype in medication-naïve adults with attention-deficit hyperactivity disorder.

BACKGROUND: Childhood-onset attention-deficit hyperactivity disorder (ADHD) in adults is clinically heterogeneous and commonly presents with different patterns of cognitive deficits. It is unclear if this clinical heterogeneity expresses a dimensional or categorical difference in ADHD. METHODS: We first studied differences in functional connectivity in multi-echo resting-state functional magnetic resonance imaging (rs-fMRI) acquired from 80 medication-naïve adults with ADHD and 123 matched healthy controls. We then used canonical correlation analysis (CCA) to identify latent relationships between symptoms and patterns of altered functional connectivity (dimensional biotype) in patients. Clustering methods were implemented to test if the individual associations between resting-state brain connectivity and symptoms reflected a non-overlapping categorical biotype. RESULTS: Adults with ADHD showed stronger functional connectivity compared to healthy controls, predominantly between the default-mode, cingulo-opercular and subcortical networks. CCA identified a single mode of brain-symptom co-variation, corresponding to an ADHD dimensional biotype. This dimensional biotype is characterized by a unique combination of altered connectivity correlating with symptoms of hyperactivity-impulsivity, inattention, and intelligence. Clustering analyses did not support the existence of distinct categorical biotypes of adult ADHD. CONCLUSIONS: Overall, our data advance a novel finding that the reduced functional segregation between default-mode and cognitive control networks supports a clinically important dimensional biotype of childhood-onset adult ADHD. Despite the heterogeneity of its presentation, our work suggests that childhood-onset adult ADHD is a single disorder characterized by dimensional brain-symptom mediators.

Consistency-based thresholding of the human connectome.

Densely seeded probabilistic tractography yields weighted networks that are nearly fully connected, hence containing many spurious fibers. It is thus necessary to prune spurious connections from probabilistically-derived networks to obtain a more reliable overall estimate of the connectivity. A standard method is to threshold by weight, keeping only the strongest edges. Here, by measuring the consistency of edge weights across subjects, we propose a new thresholding method that aims to reduce the rate of false-positives in group-averaged connectivity matrices. Close inspection of the relationship between consistency, weight, and distance suggests that the most consistent edges are in fact those that are strong for their length, rather than simply strong overall. Hence retaining the most consistent edges preserves more long-distance connections than traditional weight-based thresholding, which penalizes long connections for being weak regardless of anatomy. By comparing our thresholded networks to mouse and macaque tracer data, we also show that consistency-based thresholding exhibits the species-invariant exponential decay of connection weights with distance, while weight-based thresholding does not. We also show that consistency-based thresholding can be used to identify highly consistent and highly inconsistent subnetworks across subjects, enabling more nuanced analyses of group-level connectivity than just the mean connectivity.

The independent influences of age and education on functional brain networks and cognition in healthy older adults.

Healthy aging is accompanied by a constellation of changes in cognitive processes and alterations in functional brain networks. The relationships between brain networks and cognition during aging in later life are moderated by demographic and environmental factors, such as prior education, in a poorly understood manner. Using multivariate analyses, we identified three latent patterns (or modes) linking resting-state functional connectivity to demographic and cognitive measures in 101 cognitively normal elders. The first mode (P = 0.00043) captures an opposing association between age and core cognitive processes such as attention and processing speed on functional connectivity patterns. The functional subnetwork expressed by this mode links bilateral sensorimotor and visual regions through key areas such as the parietal operculum. A strong, independent association between years of education and functional connectivity loads onto a second mode (P = 0.012), characterized by the involvement of key hub regions. A third mode (P = 0.041) captures weak, residual brain-behavior relations. Our findings suggest that circuits supporting lower level cognitive processes are most sensitive to the influence of age in healthy older adults. Education, and to a lesser extent, executive functions, load independently onto functional networks-suggesting that the moderating effect of education acts upon networks distinct from those vulnerable with aging. This has important implications in understanding the contribution of education to cognitive reserve during healthy aging. Hum Brain Mapp 38:5094-5114, 2017. © 2017 Wiley Periodicals, Inc.

The contribution of geometry to the human connectome.

The human connectome is a topologically complex, spatially embedded network. While its topological properties have been richly characterized, the constraints imposed by its spatial embedding are poorly understood. By applying a novel resampling method to tractography data, we show that the brain's spatial embedding makes a major, but not definitive, contribution to the topology of the human connectome. We first identify where the brain's structural hubs would likely be located if geometry was the sole determinant of brain topology. Empirical networks show a widespread shift away from this geometric center toward more peripheral interconnected skeletons in each hemisphere, with discrete clusters around the anterior insula, and the anterior and posterior midline regions of the cortex. A relatively small number of strong inter-hemispheric connections assimilate these intra-hemispheric structures into a rich club, whose connections are locally more clustered but globally longer than predicted by geometry. We also quantify the extent to which the segregation, integration, and modularity of the human brain are passively inherited from its geometry. These analyses reveal novel insights into the influence of spatial geometry on the human connectome, highlighting specific topological features that likely confer functional advantages but carry an additional metabolic cost.

The organisation of the elderly connectome.

Investigations of the human connectome have elucidated core features of adult structural networks, particularly the crucial role of hub-regions. However, little is known regarding network organisation of the healthy elderly connectome, a crucial prelude to the systematic study of neurodegenerative disorders. Here, whole-brain probabilistic tractography was performed on high-angular diffusion-weighted images acquired from 115 healthy elderly subjects (age 76-94 years; 65 females). Structural networks were reconstructed between 512 cortical and subcortical brain regions. We sought to investigate the architectural features of hub-regions, as well as left-right asymmetries, and sexual dimorphisms. We observed that the topology of hub-regions is consistent with a young adult population, and previously published adult connectomic data. More importantly, the architectural features of hub connections reflect their ongoing vital role in network communication. We also found substantial sexual dimorphisms, with females exhibiting stronger inter-hemispheric connections between cingulate and prefrontal cortices. Lastly, we demonstrate intriguing left-lateralized subnetworks consistent with the neural circuitry specialised for language and executive functions, whilst rightward subnetworks were dominant in visual and visuospatial streams. These findings provide insights into healthy brain ageing and provide a benchmark for the study of neurodegenerative disorders such as Alzheimer's disease (AD) and frontotemporal dementia (FTD).

The neural substrates of transdiagnostic cognitive-linguistic heterogeneity in primary progressive aphasia.

BACKGROUND: Clinical variants of primary progressive aphasia (PPA) are diagnosed based on characteristic patterns of language deficits, supported by corresponding neural changes on brain imaging. However, there is (i) considerable phenotypic variability within and between each diagnostic category with partially overlapping profiles of language performance between variants and (ii) accompanying non-linguistic cognitive impairments that may be independent of aphasia magnitude and disease severity. The neurobiological basis of this cognitive-linguistic heterogeneity remains unclear. Understanding the relationship between these variables would improve PPA clinical/research characterisation and strengthen clinical trial and symptomatic treatment design. We address these knowledge gaps using a data-driven transdiagnostic approach to chart cognitive-linguistic differences and their associations with grey/white matter degeneration across multiple PPA variants. METHODS: Forty-seven patients (13 semantic, 15 non-fluent, and 19 logopenic variant PPA) underwent assessment of general cognition, errors on language performance, and structural and diffusion magnetic resonance imaging to index whole-brain grey and white matter changes. Behavioural data were entered into varimax-rotated principal component analyses to derive orthogonal dimensions explaining the majority of cognitive variance. To uncover neural correlates of cognitive heterogeneity, derived components were used as covariates in neuroimaging analyses of grey matter (voxel-based morphometry) and white matter (network-based statistics of structural connectomes). RESULTS: Four behavioural components emerged: general cognition, semantic memory, working memory, and motor speech/phonology. Performance patterns on the latter three principal components were in keeping with each variant's characteristic profile, but with a spectrum rather than categorical distribution across the cohort. General cognitive changes were most marked in logopenic variant PPA. Regardless of clinical diagnosis, general cognitive impairment was associated with inferior/posterior parietal grey/white matter involvement, semantic memory deficits with bilateral anterior temporal grey/white matter changes, working memory impairment with temporoparietal and frontostriatal grey/white matter involvement, and motor speech/phonology deficits with inferior/middle frontal grey matter alterations. CONCLUSIONS: Cognitive-linguistic heterogeneity in PPA closely relates to individual-level variations on multiple behavioural dimensions and grey/white matter degeneration of regions within and beyond the language network. We further show that employment of transdiagnostic approaches may help to understand clinical symptom boundaries and reveal clinical and neural profiles that are shared across categorically defined variants of PPA.

Longitudinal Changes in Structural Connectivity in Young People at High Genetic Risk for Bipolar Disorder.

OBJECTIVE: Recent studies of patients with bipolar disorder or at high genetic risk reveal structural dysconnections among key brain networks supporting cognitive and affective processes. Understanding the longitudinal trajectories of these networks across the peak age range of bipolar disorder onset could inform mechanisms of illness onset or resilience. METHODS: Longitudinal diffusion-weighted MRI and phenotypic data were acquired at baseline and after 2 years in 183 individuals ages 12-30 years in two cohorts: 97 unaffected individuals with a first-degree relative with bipolar disorder (the high-risk group) and 86 individuals with no family history of mental illness (the control group). Whole-brain structural networks were derived using tractography, and longitudinal changes in these networks were studied using network-based statistics and mixed linear models. RESULTS: Both groups showed widespread longitudinal changes, comprising both increases and decreases in structural connectivity, consistent with a shared neurodevelopmental process. On top of these shared changes, high-risk participants showed weakening of connectivity in a network encompassing the left inferior and middle frontal areas, left striatal and thalamic structures, the left fusiform, and right parietal and occipital regions. Connections among these regions strengthened in the control group, whereas they weakened in the high-risk group, shifting toward a cohort with established bipolar disorder. There was marginal evidence for even greater network weakening in those who had their first manic or hypomanic episode before follow-up. CONCLUSIONS: Neurodevelopment from adolescence into early adulthood is associated with a substantial reorganization of structural brain networks. Differences in these maturational processes occur in a multisystem network in individuals at high genetic risk of bipolar disorder. This may represent a novel candidate to understand resilience and predict conversion to bipolar disorder.

The neurophysiological effect of NMDA-R antagonism of frontotemporal lobar degeneration is conditional on individual GABA concentration.

There is a pressing need to accelerate therapeutic strategies against the syndromes caused by frontotemporal lobar degeneration, including symptomatic treatments. One approach is for experimental medicine, coupling neurophysiological studies of the mechanisms of disease with pharmacological interventions aimed at restoring neurochemical deficits. Here we consider the role of glutamatergic deficits and their potential as targets for treatment. We performed a double-blind placebo-controlled crossover pharmaco-magnetoencephalography study in 20 people with symptomatic frontotemporal lobar degeneration (10 behavioural variant frontotemporal dementia, 10 progressive supranuclear palsy) and 19 healthy age- and gender-matched controls. Both magnetoencephalography sessions recorded a roving auditory oddball paradigm: on placebo or following 10 mg memantine, an uncompetitive NMDA-receptor antagonist. Ultra-high-field magnetic resonance spectroscopy confirmed lower concentrations of GABA in the right inferior frontal gyrus of people with frontotemporal lobar degeneration. While memantine showed a subtle effect on early-auditory processing in patients, there was no significant main effect of memantine on the magnitude of the mismatch negativity (MMN) response in the right frontotemporal cortex in patients or controls. However, the change in the right auditory cortex MMN response to memantine (vs. placebo) in patients correlated with individuals' prefrontal GABA concentration. There was no moderating effect of glutamate concentration or cortical atrophy. This proof-of-concept study demonstrates the potential for baseline dependency in the pharmacological restoration of neurotransmitter deficits to influence cognitive neurophysiology in neurodegenerative disease. With changes to multiple neurotransmitters in frontotemporal lobar degeneration, we suggest that individuals' balance of excitation and inhibition may determine drug efficacy, with implications for drug selection and patient stratification in future clinical trials.

Longitudinal Changes in Whole-Brain Functional Connectivity Strength Patterns and the Relationship With the Global Cognitive Decline in Older Adults.

Aging is associated with changes in brain functional patterns as well as cognition. The present research sought to investigate longitudinal changes in whole brain functional connectivity strength (FCS) and cognitive performance scores in very old cognitively unimpaired individuals. We studied 34 cognitively normal elderly individuals at both baseline and 4-year follow-up (baseline age = 78 ± 3.14 years) with resting-state functional magnetic resonance imaging (r-fMRI), structural MRI scans, and neuropsychological assessments conducted. Voxel-based whole brain FCS was calculated and we found that bilateral superior parietal and medial frontal regions showed decreased FCS, while the supplementary motor area (SMA) and insula showed increased FCS with age, along with a decrease in bilateral prefrontal cortical thickness. The changes of FCS in left precuneus were associated with an aging-related decline in global cognition. Taken together, our results suggest changes in FCS with aging with the precuneus as a hub and this may underlie changes in global cognition that accompany aging. These findings help better understand the normal aging mechanism.

Development of frontoparietal connectivity predicts longitudinal symptom changes in young people with autism spectrum disorder.

Structural neuroimaging studies suggest altered brain maturation in autism spectrum disorder (ASD) compared with typically developing controls (TDC). However, the prognostic value of whole-brain structural connectivity analysis in ASD has not been established. Diffusion magnetic imaging data were acquired in 27 high-functioning young ASD participants (2 females) and 29 age-matched TDC (12 females; age 8-18 years) at baseline and again following 3-7 years. Whole-brain structural connectomes were reconstructed from these data and analyzed using a longitudinal statistical model. We identified distinct patterns of widespread brain connections that exhibited either significant increases or decreases in connectivity over time (p < 0.001). There was a significant interaction between diagnosis and time in brain development (p < 0.001). This was expressed by a decrease in structural connectivity within the frontoparietal network-and its broader connectivity-in ASD during adolescence and early adulthood. Conversely, these connections increased with time in TDC. Crucially, stronger baseline connectivity in this subnetwork predicted a lower symptom load at follow-up (p = 0.048), independent of the expression of symptoms at baseline. Our findings suggest a clinically meaningful relationship between the atypical development of frontoparietal structural connections and the dynamics of the autism phenotype through early adulthood. These results highlight a potential marker of future outcome.

The site of stimulation moderates neuropsychiatric symptoms after subthalamic deep brain stimulation for Parkinson's disease.

Deep brain stimulation of the subthalamic nucleus for Parkinson's disease is an established advanced therapy that addresses motor symptoms and improves quality of life. However, it has also been associated with neuropsychiatric symptoms such as impulsivity and hypomania. When significant, these symptoms can be distressing, necessitating psychiatric intervention. However, a comprehensive analysis of neurocognitive and neuropsychiatric outcomes with reference to the site of subthalamic stimulation has not been undertaken. We examined this matter in a consecutive sample of 64 persons with Parkinson's disease undertaking subthalamic deep brain stimulation. Participants were assessed with a battery of neuropsychiatric instruments at baseline and at repeated postoperative intervals. A psychiatrist identified patients with emergent, clinically-significant symptoms due to stimulation. The site of the active electrode contact and a simulated volume of activated tissue were evaluated with reference to putative limbic, associative and motor subregions of the subthalamic nucleus. We studied anatomical correlates of longitudinal neuropsychiatric change and delineated specific subthalamic regions associated with neuropsychiatric impairment. We tested the ability of these data to predict clinically-significant symptoms. Subthalamic stimulation within the right associative subregion was associated with inhibitory errors on the Excluded Letter Fluency task at 6-weeks (p = 0.023) and 13-weeks postoperatively (p = 0.0017). A cluster of subthalamic voxels associated with inhibitory errors was identified in the right associative and motor subregions. At 6-weeks, clinically-significant neuropsychiatric symptoms were associated with the distance of the active contact to the right associative subregion (p = 0.0026) and stimulation within the right associative subregion (p = 0.0009). At 13-weeks, clinically-significant symptoms were associated with the distance to the right (p = 0.0027) and left (p = 0.0084) associative subregions and stimulation within the right associative subregion (p = 0.0026). Discrete clusters of subthalamic voxels associated with high and low likelihood of postoperative neuropsychiatric symptoms were identified in ventromedial and dorsolateral zones, respectively. When a classifier was trained on these data, clinically-significant symptoms were predicted with an accuracy of 79%. These data underscore the importance of accurate electrode targeting, contact selection and device programming to reduce postoperative neuropsychiatric impairment. The ability to predict neuropsychiatric symptoms based on subthalamic data may permit anticipation and prevention of these occurrences, improving safety and tolerability.